1,710 research outputs found
Histogram-Aware Sorting for Enhanced Word-Aligned Compression in Bitmap Indexes
Bitmap indexes must be compressed to reduce input/output costs and minimize
CPU usage. To accelerate logical operations (AND, OR, XOR) over bitmaps, we use
techniques based on run-length encoding (RLE), such as Word-Aligned Hybrid
(WAH) compression. These techniques are sensitive to the order of the rows: a
simple lexicographical sort can divide the index size by 9 and make indexes
several times faster. We investigate reordering heuristics based on computed
attribute-value histograms. Simply permuting the columns of the table based on
these histograms can increase the sorting efficiency by 40%.Comment: To appear in proceedings of DOLAP 200
Reordering Rows for Better Compression: Beyond the Lexicographic Order
Sorting database tables before compressing them improves the compression
rate. Can we do better than the lexicographical order? For minimizing the
number of runs in a run-length encoding compression scheme, the best approaches
to row-ordering are derived from traveling salesman heuristics, although there
is a significant trade-off between running time and compression. A new
heuristic, Multiple Lists, which is a variant on Nearest Neighbor that trades
off compression for a major running-time speedup, is a good option for very
large tables. However, for some compression schemes, it is more important to
generate long runs rather than few runs. For this case, another novel
heuristic, Vortex, is promising. We find that we can improve run-length
encoding up to a factor of 3 whereas we can improve prefix coding by up to 80%:
these gains are on top of the gains due to lexicographically sorting the table.
We prove that the new row reordering is optimal (within 10%) at minimizing the
runs of identical values within columns, in a few cases.Comment: to appear in ACM TOD
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